Fourier-transform infrared spectroscopy: A universal optical sensing technique with auspicious application prospects in the diagnosis and management of autoimmune diseases

Alkhuder, Khaled

doi:10.1016/j.pdpdt.2023.103606

Cited by 3 publications

(1 citation statement)

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“…The use of spectroscopic techniques to analyse biological samples, known as biospectroscopy, has gained great attention in recent decades since it allows the investigation of diseases based on biochemical changes that occur as a consequence of pathological events 24 . Vibrational spectroscopies have been successfully applied in many studies in medical chemistry 25 since they provide alternative methods for screening, identi cation and diagnosis of diseases through simple, cost-effective and accurate methodologies. Herein, we used different chemometric methods to analyse ATR-FTIR data for the differential diagnosis of leptospirosis and dengue in patients from Colombia, an endemic country for both diseases.…”

Section: Discussionmentioning

confidence: 99%

Infrared spectroscopy and multivariate analysis applied to the differential diagnosis of leptospirosis and dengue

Zambrano,

Trilleras,

Arana

et al. 2024

Preprint

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Dengue and leptospirosis are considered systemic and very dynamic illnesses in which a patient can rapidly progress from mild to severe conditions. Both diseases present very similar acute initial symptoms, a fact that may result in a challenging differential diagnosis at the initial phases. Herein, we present the application of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with multivariate analysis to perform differential diagnosis of leptospirosis and dengue by analysing blood plasma. The spectra of 114 samples from patients in different phases of infection (n = 43 for leptospirosis and n = 71 for dengue) were analysed by either linear or quadratic discrimination in association with genetic algorithms, successive projection algorithms and principal component analysis for feature selection/extraction. The best model, GA-QDA, achieved outstanding results in terms of maximum (100%) sensitivity, specificity and accuracy for classifying both classes by using only 31 spectral variables. The ANOVA calculations, at a confidence level of 95%, highlighted a set of 10 variables selected by the GA-QDA model (1296 cm-1, 1612 cm-1, 1673 cm-1, 1677 cm-1, 1678 cm-1, 1689 cm-1, 1694 cm-1, 1711 cm-1, 1713 cm-1 and 1719 cm-1) with significant differences in the absorbance means between the Leptospirosis and Dengue classes. These specific wavenumbers represent the most useful spectral information accounting for the biochemical changes that mark a specific infection. These remarkable results obtained in this pilot study highlight the viability of this methodology to be applied in clinical practice to serve as a simple and accurate test for discriminating between the two illnesses.

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Section: Discussionmentioning

confidence: 99%